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https://issues.apache.org/jira/browse/ACCUMULO-1083?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Luke Brassard updated ACCUMULO-1083:
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    Attachment: walog-replication-factor-performance.jpg

Here are the updated results, which show the performance gains expected from 
tweaking the {{tserver.wal.replication}} setting.

||version||walog replication||MB/sec/node||entries ingested||
|accumulo-1.4.2|default|6.691|1024000000|
|accumulo-1.4.2|false|23.583|4096000000|
|accumulo-1.5.0-SNAPSHOT|default|5.734|1024000000|
|accumulo-1.5.0-SNAPSHOT|2|8.366|1024000000|
|accumulo-1.5.0-SNAPSHOT|1|14.883|1024000000|
|accumulo-1.5.0-SNAPSHOT|false|27.321|4096000000|

I ran the tests and cleared the results

I've included another screenshot that illustrates the tests with walogs at 2, 
1, and none.
                
> add concurrency to HDFS write-ahead log
> ---------------------------------------
>
>                 Key: ACCUMULO-1083
>                 URL: https://issues.apache.org/jira/browse/ACCUMULO-1083
>             Project: Accumulo
>          Issue Type: Improvement
>          Components: tserver
>            Reporter: Adam Fuchs
>             Fix For: 1.6.0
>
>         Attachments: walog-performance.jpg, 
> walog-replication-factor-performance.jpg
>
>
> When running tablet servers on beefy nodes (lots of disks), the write-ahead 
> log can be a serious bottleneck. Today we ran a continuous ingest test of 
> 1.5-SNAPSHOT on an 8-node (plus a master node) cluster in which the nodes had 
> 32 cores and 15 drives each. Running with write-ahead log off resulted in a 
> >4x performance improvement sustained over a long period.
> I believe the culprit is that the WAL is only using one file at a time per 
> tablet server, which means HDFS is only appending to one drive (plus 
> replicas). If we increase the number of concurrent WAL files supported on a 
> tablet server we could probably drastically improve the performance on 
> systems with many disks. As it stands, I believe Accumulo is significantly 
> more optimized for a larger number of smaller nodes (3-4 drives).

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